Is the monetary policy regime just a sideshow in the long-run evolution of real interest rates? The long-run path of the real interest rate depends in part on the monetary policy rule in force.
Real interest rate determination: saving and investment?
A historical perspective
Based on historical data for a large cross-section of countries, we find that the ability of savings and investment fundamentals to explain real interest rates is limited, while the ability of monetary regimes is more evident. In contrast, a large part of the empirical studies outlined above concentrate on the period since the mid-1980s, when real interest rates have been falling.
The safe asset shortage hypothesis: a critique
Equity risk premium estimates are notoriously sensitive to the model used and the dispersion is extremely wide (Chart 6, left panel). In fact, a cursory inspection of the evolution of various risk spreads suggests that the SAS story is not so plausible.
Real interest rate determination: financial and monetary factors?
Setting the stage: compasses and monetary policy non-neutrality
We find that this shock explains only a small part of the evolution of the system variables. In particular, it explains less than 10 basis points of the fall in natural interest rates since 2011, while the three other shocks together explain as much as 1.20 percentage points. But inflation need not be the sole indicator of market deviations from its natural course.
And it is even recognized by proponents of the savings-investment view of interest rate setting (e.g. Summers (2015)). Conceptually, the pairing raises questions about the usefulness of the natural velocity standard definition. This suggests that it would make sense to extend the definition of the natural rate of interest to a notion of financial equilibrium.
This significantly reduces the relevance of the additional information provided by the financial factors and of intertemporal trade-offs. The importance of the financial cycle is underlined by the evidence showing that crisis-related failures often generate long-term if not permanent output costs (e.g. BCBS (2010), Cerra and Saxena (2008), Blanchard et al (2015)) . Booms sow the seeds of subsequent failures due to the vulnerabilities that build up over time.
Monetary policy and the financial cycle: an empirical model
To capture the salient features of the financial cycle and its interaction with policy and the real economy, we construct a more articulated empirical model in Juselius et al (2017). The starting point is a characterization of the financial cycle based on two stable long-term (co-integrating) relationships. It also implies that the current state of the financial cycle predicts the subsequent output trajectories fairly well.
This simply reflects the fact that asset prices tend to outpace the credit-to-GDP ratio during boom times, even as the ratio rises above historical trends. Finally, a source of profit is that policy helps moderate the financial cycle (bottom panels). 1 In a hypothetical experiment, we set the policy according to the extended Taylor rule, which takes into account the financially neutral natural rate, the financially neutral output gap and the debt service gap according to equation (11).
We retain the historical errors to derive the evolution of the variables in the counterfactual. 22 This reflects the flattening of the Phillips curve and the overall improvement in output performance. 23 Filardo and Rungcharoenkitkul (2016) reach similar conclusions using optimal control techniques based on the more stylized version of the financial cycle illustrated in Chart 11.
Monetary policy and the financial cycle: a theoretical model
The Lucas critique, in particular, may be exaggerated.24 As the public becomes aware of the central bank's response function, it may even increase policy effectiveness, just as credibility against inflation increases the likelihood of second-round effects in wages and prices decrease. . They can only do this by borrowing from banks whose financing costs are determined by the central bank. However, low interest rates also increase the number of bad companies in the overall loan pool and gradually weaken the banking sector by undermining its profits.
As a result, there is a trade-off between short- and long-run output – a major constraint for the central bank. As the boom continues, excessive competition diminishes 𝐾 and leads to ever-higher policy rates as the central bank ramps up its efforts to curb the boom. Once the level of bank capital drops to a critically low level, failure becomes so imminent that the marginal benefit of leaning no longer outweighs the short-term cost to the central bank.
At this point, the central bank moves to a low interest rate in anticipation of a collapse. In the event of a crash, the central bank simply sets the interest rate low to increase the short-term payout—the best it can do under the circumstances. Meanwhile, the most forward-looking central bank avoids collapse in the first 50 periods and manages to keep interest rates high throughout the middle simulation.
Policy implications
How useful is the natural interest rate as a policy benchmark?
The model emphasizes the role of the monetary policy response function in determining the average level of (real) interest rates. The trend decline in interest rates may reflect the need for monetary policy to come to the rescue in those situations (e.g. early 1990s and during the economic crisis; Drehmann et al (2012). The possibility of different paths depending on the order of monetary policy measures even raise the prospect of the economy developing along unsustainable paths.
In the language of our model, monetary policy can act like a forcing variable that maintains the system at an arbitrary level for a long period of time. 30 From this perspective, references to "passive" monetary policy as just an innocent bystander to a falling equilibrium real rate are misleading (eg Kocherlakota (2013)). On the one hand, monetary policy is considered "passive", simply following an exogenous natural course and having little influence on real outcomes in the medium term.
On the other hand, monetary policy is seen as crucial in stopping the GFC, preventing a much worse outcome, and as "the only game in town", paving the way for a sustainable recovery through its strong influence on the global financial conditions. in strong headwind. All this suggests that there is prima facie reason for monetary policy to pay more attention to the financial cycle than in the past. We may be underestimating the impact of benign disinflationary forces, particularly related to globalization and technology, and overestimating the ability of monetary policy to fine-tune inflation, especially to steer it towards targets in the face of strong headwinds.
Adjusting policy frameworks
In technical terms, the interaction between monetary policy and the financial cycle generates path dependency. Adrian, T and F Duarte (2017): “Financial Fragility and Monetary Policy,” Federal Reserve Bank of New York Staff Reports, No. 804, September. Paper presented at the 21st Annual Conference of the Central Bank of Chile on Monetary Policy and Financial Stability: Transmission Mechanisms and Policy Implications, Santiago, Chile, November 16–17, 2017.
Carvalho, C, A Ferrero and F Nechio (2016): "Demography and Real Interest Rates: Inspecting the Mechanism", Federal Reserve Bank of San Francisco Working Papers, No. 2016-5. Christiano, L., C Ilut, R Motto and M Rostagno (2008): “Monetary policy and stock market boom-bust cycles”, ECB Working Papers, No. 955. Drehmann M, C Borio and K Tsatsaronis (2012): “ Characterizing the financial cycle: don't miss the medium term!”, BIS Working Papers, no.
Laubach T en Williams J (2015): "Measuring the natural rate of interest redux", Federal Reserve bank of San Francisco Working Papers, nr. Juselius, M en M Drehmann (2015): "Hefboomdynamiek en de reële schuldenlast ”, BIS Working Papers, nr. Laubach, T en Williams J (2015): “Measuring the natural rate of interest redux“, Federal Reserve Bank of San Francisco Working Papers, nr. 2015-16.
An empirical analysis of the safe asset shortage hypothesis
In the case of the United States, both short-term and 5-year 5-year-ahead real rates have fallen in recent decades, with monetary policy's influence on the short-term rate clearly substantial (Chart A1). 37 Proponents of the SAS view sometimes refer to short-term interest rates to motivate their discussion. For the safe asset and natural rate shocks, which in theory should have more persistent effects, we set the sign limits for 6 months after the occurrence of the shocks.
Graphs A2 show the impulse response functions of the four shocks, together with a one standard error band. The shock also lowers 5y5y in the short term, likely reflecting its impact on the risk premium component of the forward rate. Finally, the global risk appetite shock does not materially affect the US futures premium and 5y5y, confirming the interpretation of the shock.
Pay particular attention to the top left panel, which shows a historical breakdown of the 5-year 5-year forward rate, our proxy for the natural rate. Most of the reduction in this variable can be explained by shocks to r* and years to safety, with the safe asset shock contributing little. Even during the 2011 euro crisis, when safe-haven concerns probably peaked, the contribution of r* and year shocks to safety was large.
A model of monetary policy and the financial cycle
We assume 𝑎 > 𝑏 that the economy needs to restore bank capital lost over time before it can recover. The assumption means that both regimes are persistent. The development of bank capital is given by Since they only live for two periods, future policy actions, regimes and bank capital are not included in their decisions.41 This allows the equilibrium to be calculated from period to period for a given policy rate 𝑅𝑡𝑑.
The period payoff is simply defined as the sum of the utility value of all economic actors. A sustained low policy interest rate gradually erodes the level of bank capital, eventually crashing the economy into a bust. We numerically solve this dynamic programming problem and obtain the optimal choice of 𝑅𝑡𝑑 as a function of bank capital and the regime (left panel of Graph 13 in the main text.).
Setting low interest rates increases the immediate payout, but at the cost of deteriorating bank capital and thus a greater likelihood of falling into a disruptive crisis in the future. In fact, optimal policies require interest rates slightly higher than the period-payout-maximizing level (𝑅𝑡𝑑≈ 1 as outlined above) to internalize the effect of bank competition and "lean against" the financial one. Our model simply assumes that bank capital can be accurately observed (profits measured correctly), but nevertheless booms persist for reasons other than informational frictions.
